Počet záznamů: 1  

Action potential propagation and synchronisation in myelinated axons

  1. 1.
    0546903 - ÚI 2022 US eng J - Článek v odborném periodiku
    Schmidt, Helmut - Knösche, T.R.
    Action potential propagation and synchronisation in myelinated axons.
    PLoS Computational Biology. Roč. 15, č. 10 (2019), č. článku e1007004. ISSN 1553-734X. E-ISSN 1553-7358
    Klíčová slova: nerve-fibers * conduction-velocity * membrane currents * electric-fields * white-matter * diameter * model * impulse * voltage * cable
    Impakt faktor: 4.700, rok: 2019

    With the advent of advanced MRI techniques it has become possible to study axonal white matter non-invasively and in great detail. Measuring the various parameters of the long-range connections of the brain opens up the possibility to build and refine detailed models of large-scale neuronal activity. One particular challenge is to find a mathematical description of action potential propagation that is sufficiently simple, yet still biologically plausible to model signal transmission across entire axonal fibre bundles. We develop a mathematical framework in which we replace the Hodgkin-Huxley dynamics by a spike-diffuse-spike model with passive sub-threshold dynamics and explicit, threshold-activated ion channel currents. This allows us to study in detail the influence of the various model parameters on the action potential velocity and on the entrainment of action potentials between ephaptically coupled fibres without having to recur to numerical simulations. Specifically, we recover known results regarding the influence of axon diameter, node of Ranvier length and internode length on the velocity of action potentials. Additionally, we find that the velocity depends more strongly on the thickness of the myelin sheath than was suggested by previous theoretical studies. We further explain the slowing down and synchronisation of action potentials in ephaptically coupled fibres by their dynamic interaction. In summary, this study presents a solution to incorporate detailed axonal parameters into a whole-brain modelling framework.
    Trvalý link: http://hdl.handle.net/11104/0323288

     
     
Počet záznamů: 1  

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